"""Experimental pipeline API functionality. Be careful with this API, it's subject to change."""

from __future__ import annotations

import datetime
import operator
import re
from collections import deque
from collections.abc import Callable, Container
from dataclasses import dataclass
from functools import cached_property, partial
from re import Pattern
from types import EllipsisType
from typing import TYPE_CHECKING, Annotated, Any, Generic, Protocol, TypeAlias, TypeVar, overload

import annotated_types

if TYPE_CHECKING:
    from pydantic import GetCoreSchemaHandler

from pydantic_core import PydanticCustomError
from pydantic_core import core_schema as cs

from pydantic import Strict

__all__ = ['validate_as', 'validate_as_deferred', 'transform']


@dataclass(frozen=True, slots=True)
class _ValidateAs:
    tp: type[Any]
    strict: bool = False


@dataclass
class _ValidateAsDefer:
    func: Callable[[], type[Any]]

    @cached_property
    def tp(self) -> type[Any]:
        return self.func()


@dataclass(frozen=True, slots=True)
class _Transform:
    func: Callable[[Any], Any]


@dataclass(frozen=True, slots=True)
class _PipelineOr:
    left: _Pipeline[Any, Any]
    right: _Pipeline[Any, Any]


@dataclass(frozen=True, slots=True)
class _PipelineAnd:
    left: _Pipeline[Any, Any]
    right: _Pipeline[Any, Any]


@dataclass(frozen=True, slots=True)
class _Eq:
    value: Any


@dataclass(frozen=True, slots=True)
class _NotEq:
    value: Any


@dataclass(frozen=True, slots=True)
class _In:
    values: Container[Any]


@dataclass(frozen=True, slots=True)
class _NotIn:
    values: Container[Any]


_ConstraintAnnotation: TypeAlias = (
    annotated_types.Le
    | annotated_types.Ge
    | annotated_types.Lt
    | annotated_types.Gt
    | annotated_types.Len
    | annotated_types.MultipleOf
    | annotated_types.Timezone
    | annotated_types.Interval
    | annotated_types.Predicate
    |
    # common predicates not included in annotated_types
    _Eq
    | _NotEq
    | _In
    | _NotIn
    |
    # regular expressions
    Pattern[str]
)


@dataclass(frozen=True, slots=True)
class _Constraint:
    constraint: _ConstraintAnnotation


_Step: TypeAlias = _ValidateAs | _ValidateAsDefer | _Transform | _PipelineOr | _PipelineAnd | _Constraint

_InT = TypeVar('_InT')
_OutT = TypeVar('_OutT')
_NewOutT = TypeVar('_NewOutT')


class _FieldTypeMarker:
    pass


# TODO: ultimately, make this public, see https://github.com/pydantic/pydantic/pull/9459#discussion_r1628197626
# Also, make this frozen eventually, but that doesn't work right now because of the generic base
# Which attempts to modify __orig_base__ and such.
# We could go with a manual freeze, but that seems overkill for now.
@dataclass(slots=True)
class _Pipeline(Generic[_InT, _OutT]):
    """Abstract representation of a chain of validation, transformation, and parsing steps."""

    _steps: tuple[_Step, ...]

    def transform(
        self,
        func: Callable[[_OutT], _NewOutT],
    ) -> _Pipeline[_InT, _NewOutT]:
        """Transform the output of the previous step.

        If used as the first step in a pipeline, the type of the field is used.
        That is, the transformation is applied to after the value is parsed to the field's type.
        """
        return _Pipeline[_InT, _NewOutT](self._steps + (_Transform(func),))

    @overload
    def validate_as(self, tp: type[_NewOutT], *, strict: bool = False) -> _Pipeline[_InT, _NewOutT]: ...

    @overload
    def validate_as(
        self,
        tp: EllipsisType,
        *,
        strict: bool = False,
    ) -> _Pipeline[_InT, Any]: ...

    # TODO PEP 747: use TypeForm to properly type Annotated aliases (e.g. NewPath, FilePath).
    # This fallback accepts any type expression but loses generic type inference.
    @overload
    def validate_as(self, tp: Any, *, strict: bool = ...) -> _Pipeline[_InT, Any]: ...

    def validate_as(self, tp: type[_NewOutT] | EllipsisType | Any, *, strict: bool = False) -> _Pipeline[_InT, Any]:  # type: ignore
        """Validate / parse the input into a new type.

        If no type is provided, the type of the field is used.

        Types are parsed in Pydantic's `lax` mode by default,
        but you can enable `strict` mode by passing `strict=True`.
        """
        if isinstance(tp, EllipsisType):
            return _Pipeline[_InT, Any](self._steps + (_ValidateAs(_FieldTypeMarker, strict=strict),))
        return _Pipeline[_InT, _NewOutT](self._steps + (_ValidateAs(tp, strict=strict),))

    def validate_as_deferred(self, func: Callable[[], type[_NewOutT]]) -> _Pipeline[_InT, _NewOutT]:
        """Parse the input into a new type, deferring resolution of the type until the current class
        is fully defined.

        This is useful when you need to reference the class in it's own type annotations.
        """
        return _Pipeline[_InT, _NewOutT](self._steps + (_ValidateAsDefer(func),))

    # constraints
    @overload
    def constrain(self: _Pipeline[_InT, _NewOutGe], constraint: annotated_types.Ge) -> _Pipeline[_InT, _NewOutGe]: ...

    @overload
    def constrain(self: _Pipeline[_InT, _NewOutGt], constraint: annotated_types.Gt) -> _Pipeline[_InT, _NewOutGt]: ...

    @overload
    def constrain(self: _Pipeline[_InT, _NewOutLe], constraint: annotated_types.Le) -> _Pipeline[_InT, _NewOutLe]: ...

    @overload
    def constrain(self: _Pipeline[_InT, _NewOutLt], constraint: annotated_types.Lt) -> _Pipeline[_InT, _NewOutLt]: ...

    @overload
    def constrain(
        self: _Pipeline[_InT, _NewOutLen], constraint: annotated_types.Len
    ) -> _Pipeline[_InT, _NewOutLen]: ...

    @overload
    def constrain(
        self: _Pipeline[_InT, _NewOutT], constraint: annotated_types.MultipleOf
    ) -> _Pipeline[_InT, _NewOutT]: ...

    @overload
    def constrain(
        self: _Pipeline[_InT, _NewOutDatetime], constraint: annotated_types.Timezone
    ) -> _Pipeline[_InT, _NewOutDatetime]: ...

    @overload
    def constrain(self: _Pipeline[_InT, _OutT], constraint: annotated_types.Predicate) -> _Pipeline[_InT, _OutT]: ...

    @overload
    def constrain(
        self: _Pipeline[_InT, _NewOutInterval], constraint: annotated_types.Interval
    ) -> _Pipeline[_InT, _NewOutInterval]: ...

    @overload
    def constrain(self: _Pipeline[_InT, _OutT], constraint: _Eq) -> _Pipeline[_InT, _OutT]: ...

    @overload
    def constrain(self: _Pipeline[_InT, _OutT], constraint: _NotEq) -> _Pipeline[_InT, _OutT]: ...

    @overload
    def constrain(self: _Pipeline[_InT, _OutT], constraint: _In) -> _Pipeline[_InT, _OutT]: ...

    @overload
    def constrain(self: _Pipeline[_InT, _OutT], constraint: _NotIn) -> _Pipeline[_InT, _OutT]: ...

    @overload
    def constrain(self: _Pipeline[_InT, _NewOutT], constraint: Pattern[str]) -> _Pipeline[_InT, _NewOutT]: ...

    def constrain(self, constraint: _ConstraintAnnotation) -> Any:
        """Constrain a value to meet a certain condition.

        We support most conditions from `annotated_types`, as well as regular expressions.

        Most of the time you'll be calling a shortcut method like `gt`, `lt`, `len`, etc
        so you don't need to call this directly.
        """
        return _Pipeline[_InT, _OutT](self._steps + (_Constraint(constraint),))

    def predicate(self: _Pipeline[_InT, _NewOutT], func: Callable[[_NewOutT], bool]) -> _Pipeline[_InT, _NewOutT]:
        """Constrain a value to meet a certain predicate."""
        return self.constrain(annotated_types.Predicate(func))

    def gt(self: _Pipeline[_InT, _NewOutGt], gt: _NewOutGt) -> _Pipeline[_InT, _NewOutGt]:
        """Constrain a value to be greater than a certain value."""
        return self.constrain(annotated_types.Gt(gt))

    def lt(self: _Pipeline[_InT, _NewOutLt], lt: _NewOutLt) -> _Pipeline[_InT, _NewOutLt]:
        """Constrain a value to be less than a certain value."""
        return self.constrain(annotated_types.Lt(lt))

    def ge(self: _Pipeline[_InT, _NewOutGe], ge: _NewOutGe) -> _Pipeline[_InT, _NewOutGe]:
        """Constrain a value to be greater than or equal to a certain value."""
        return self.constrain(annotated_types.Ge(ge))

    def le(self: _Pipeline[_InT, _NewOutLe], le: _NewOutLe) -> _Pipeline[_InT, _NewOutLe]:
        """Constrain a value to be less than or equal to a certain value."""
        return self.constrain(annotated_types.Le(le))

    def len(self: _Pipeline[_InT, _NewOutLen], min_len: int, max_len: int | None = None) -> _Pipeline[_InT, _NewOutLen]:
        """Constrain a value to have a certain length."""
        return self.constrain(annotated_types.Len(min_len, max_len))

    @overload
    def multiple_of(self: _Pipeline[_InT, _NewOutDiv], multiple_of: _NewOutDiv) -> _Pipeline[_InT, _NewOutDiv]: ...

    @overload
    def multiple_of(self: _Pipeline[_InT, _NewOutMod], multiple_of: _NewOutMod) -> _Pipeline[_InT, _NewOutMod]: ...

    def multiple_of(self: _Pipeline[_InT, Any], multiple_of: Any) -> _Pipeline[_InT, Any]:
        """Constrain a value to be a multiple of a certain number."""
        return self.constrain(annotated_types.MultipleOf(multiple_of))

    def eq(self: _Pipeline[_InT, _OutT], value: _OutT) -> _Pipeline[_InT, _OutT]:
        """Constrain a value to be equal to a certain value."""
        return self.constrain(_Eq(value))

    def not_eq(self: _Pipeline[_InT, _OutT], value: _OutT) -> _Pipeline[_InT, _OutT]:
        """Constrain a value to not be equal to a certain value."""
        return self.constrain(_NotEq(value))

    def in_(self: _Pipeline[_InT, _OutT], values: Container[_OutT]) -> _Pipeline[_InT, _OutT]:
        """Constrain a value to be in a certain set."""
        return self.constrain(_In(values))

    def not_in(self: _Pipeline[_InT, _OutT], values: Container[_OutT]) -> _Pipeline[_InT, _OutT]:
        """Constrain a value to not be in a certain set."""
        return self.constrain(_NotIn(values))

    # timezone methods
    def datetime_tz_naive(self: _Pipeline[_InT, datetime.datetime]) -> _Pipeline[_InT, datetime.datetime]:
        """Constrain a datetime value to be timezone-naive (i.e. have no tzinfo)."""
        return self.constrain(annotated_types.Timezone(None))

    def datetime_tz_aware(self: _Pipeline[_InT, datetime.datetime]) -> _Pipeline[_InT, datetime.datetime]:
        """Constrain a datetime value to be timezone-aware (i.e. have a non-None tzinfo)."""
        return self.constrain(annotated_types.Timezone(...))

    def datetime_tz(
        self: _Pipeline[_InT, datetime.datetime], tz: datetime.tzinfo
    ) -> _Pipeline[_InT, datetime.datetime]:
        """Constrain a datetime value to have a specific timezone.

        Args:
            tz: The required timezone.
        """
        return self.constrain(annotated_types.Timezone(tz))  # type: ignore

    def datetime_with_tz(
        self: _Pipeline[_InT, datetime.datetime], tz: datetime.tzinfo | None
    ) -> _Pipeline[_InT, datetime.datetime]:
        """Transform a datetime value by replacing its timezone with the given value.

        Unlike `datetime_tz()`, this does not validate the existing timezone, it
        unconditionally sets [`tzinfo`][datetime.datetime.tzinfo] to `tz`.

        Args:
            tz: The timezone to attach to the datetime, or `None` to make it naive.
        """
        return self.transform(partial(datetime.datetime.replace, tzinfo=tz))

    # string methods
    def str_lower(self: _Pipeline[_InT, str]) -> _Pipeline[_InT, str]:
        """Transform a string value to [lowercase][str.lower]."""
        return self.transform(str.lower)

    def str_upper(self: _Pipeline[_InT, str]) -> _Pipeline[_InT, str]:
        """Transform a string value to [uppercase][str.upper]."""
        return self.transform(str.upper)

    def str_title(self: _Pipeline[_InT, str]) -> _Pipeline[_InT, str]:
        """Transform a string value to [title case][str.title]."""
        return self.transform(str.title)

    def str_strip(self: _Pipeline[_InT, str]) -> _Pipeline[_InT, str]:
        """Strip leading and trailing whitespace from a string value."""
        return self.transform(str.strip)

    def str_pattern(self: _Pipeline[_InT, str], pattern: str) -> _Pipeline[_InT, str]:
        """Constrain a string value to match a regular expression pattern.

        Args:
            pattern: The regular expression pattern the string must match.
        """
        return self.constrain(re.compile(pattern))

    def str_contains(self: _Pipeline[_InT, str], substring: str) -> _Pipeline[_InT, str]:
        """Constrain a string value to contain a given substring.

        Args:
            substring: The substring that must be present in the string.
        """
        return self.predicate(lambda v: substring in v)

    def str_starts_with(self: _Pipeline[_InT, str], prefix: str) -> _Pipeline[_InT, str]:
        """Constrain a string value to start with a given prefix.

        Args:
            prefix: The prefix the string must start with.
        """
        return self.predicate(lambda v: v.startswith(prefix))

    def str_ends_with(self: _Pipeline[_InT, str], suffix: str) -> _Pipeline[_InT, str]:
        """Constrain a string value to end with a given suffix.

        Args:
            suffix: The suffix the string must end with.
        """
        return self.predicate(lambda v: v.endswith(suffix))

    # operators
    def otherwise(self, other: _Pipeline[_OtherIn, _OtherOut]) -> _Pipeline[_InT | _OtherIn, _OutT | _OtherOut]:
        """Combine two validation chains, returning the result of the first chain if it succeeds, and the second chain if it fails."""
        return _Pipeline((_PipelineOr(self, other),))

    __or__ = otherwise

    def then(self, other: _Pipeline[_OutT, _OtherOut]) -> _Pipeline[_InT, _OtherOut]:
        """Pipe the result of one validation chain into another."""
        return _Pipeline((_PipelineAnd(self, other),))

    __and__ = then

    def __get_pydantic_core_schema__(self, source_type: Any, handler: GetCoreSchemaHandler) -> cs.CoreSchema:
        return self._apply_pipeline(handler, source_type)

    def _apply_pipeline(self, handler: GetCoreSchemaHandler, source_type: Any) -> cs.CoreSchema:
        queue = deque(self._steps)

        s = None

        while queue:
            step = queue.popleft()
            s = _apply_step(step, s, handler, source_type)

        s = s or cs.any_schema()
        return s

    def __supports_type__(self, _: _OutT) -> bool:
        raise NotImplementedError


validate_as = _Pipeline[Any, Any](()).validate_as
validate_as_deferred = _Pipeline[Any, Any](()).validate_as_deferred
transform = _Pipeline[Any, Any]((_ValidateAs(_FieldTypeMarker),)).transform


def _check_func(
    func: Callable[[Any], bool], predicate_err: str | Callable[[], str], s: cs.CoreSchema | None
) -> cs.CoreSchema:
    def handler(v: Any) -> Any:
        if func(v):
            return v
        raise ValueError(f'Expected {predicate_err if isinstance(predicate_err, str) else predicate_err()}')

    if s is None:
        return cs.no_info_plain_validator_function(handler)
    else:
        return cs.no_info_after_validator_function(handler, s)


def _apply_step(step: _Step, s: cs.CoreSchema | None, handler: GetCoreSchemaHandler, source_type: Any) -> cs.CoreSchema:
    if isinstance(step, _ValidateAs):
        s = _apply_parse(s, step.tp, step.strict, handler, source_type)
    elif isinstance(step, _ValidateAsDefer):
        s = _apply_parse(s, step.tp, False, handler, source_type)
    elif isinstance(step, _Transform):
        s = _apply_transform(s, step.func, handler)
    elif isinstance(step, _Constraint):
        s = _apply_constraint(s, step.constraint)
    elif isinstance(step, _PipelineOr):
        s = cs.union_schema(
            [step.left._apply_pipeline(handler, source_type), step.right._apply_pipeline(handler, source_type)]
        )
    else:
        assert isinstance(step, _PipelineAnd)
        s = cs.chain_schema(
            [step.left._apply_pipeline(handler, source_type), step.right._apply_pipeline(handler, source_type)]
        )
    return s


def _apply_parse(
    s: cs.CoreSchema | None,
    tp: type[Any],
    strict: bool,
    handler: GetCoreSchemaHandler,
    source_type: Any,
) -> cs.CoreSchema:
    if tp is _FieldTypeMarker:
        return cs.chain_schema([s, handler(source_type)]) if s else handler(source_type)

    if strict:
        tp = Annotated[tp, Strict()]  # type: ignore

    if s and s['type'] == 'any':
        return handler(tp)
    else:
        return cs.chain_schema([s, handler(tp)]) if s else handler(tp)


def _apply_transform(
    s: cs.CoreSchema | None, func: Callable[[Any], Any], handler: GetCoreSchemaHandler
) -> cs.CoreSchema:
    if s is None:
        return cs.no_info_plain_validator_function(func)

    if s['type'] == 'str':
        if func is str.strip:
            s = s.copy()
            s['strip_whitespace'] = True
            return s
        elif func is str.lower:
            s = s.copy()
            s['to_lower'] = True
            return s
        elif func is str.upper:
            s = s.copy()
            s['to_upper'] = True
            return s

    return cs.no_info_after_validator_function(func, s)


def _apply_constraint(  # noqa: C901
    s: cs.CoreSchema | None, constraint: _ConstraintAnnotation
) -> cs.CoreSchema:
    """Apply a single constraint to a schema."""
    # No casting of the constraints is necessary, as pydantic-core does it
    # when building the validator from the core schema:
    if isinstance(constraint, annotated_types.Gt):
        gt = constraint.gt
        if s and s['type'] in {'int', 'float', 'decimal'}:
            s = s.copy()
            s['gt'] = gt  # pyright: ignore[reportGeneralTypeIssues]
        else:

            def check_gt(v: Any) -> bool:
                return v > gt

            s = _check_func(check_gt, f'> {gt}', s)
    elif isinstance(constraint, annotated_types.Ge):
        ge = constraint.ge
        if s and s['type'] in {'int', 'float', 'decimal'}:
            s = s.copy()
            s['ge'] = ge  # pyright: ignore[reportGeneralTypeIssues]
        else:

            def check_ge(v: Any) -> bool:
                return v >= ge

            s = _check_func(check_ge, f'>= {ge}', s)
    elif isinstance(constraint, annotated_types.Lt):
        lt = constraint.lt
        if s and s['type'] in {'int', 'float', 'decimal'}:
            s = s.copy()
            s['lt'] = lt  # pyright: ignore[reportGeneralTypeIssues]
        else:

            def check_lt(v: Any) -> bool:
                return v < lt

            s = _check_func(check_lt, f'< {lt}', s)
    elif isinstance(constraint, annotated_types.Le):
        le = constraint.le
        if s and s['type'] in {'int', 'float', 'decimal'}:
            s = s.copy()
            s['le'] = le  # pyright: ignore[reportGeneralTypeIssues]
        else:

            def check_le(v: Any) -> bool:
                return v <= le

            s = _check_func(check_le, f'<= {le}', s)
    elif isinstance(constraint, annotated_types.Len):
        min_len = constraint.min_length
        max_len = constraint.max_length

        if s and s['type'] in {'str', 'list', 'tuple', 'set', 'frozenset', 'dict'}:
            assert (
                s['type'] == 'str'
                or s['type'] == 'list'
                or s['type'] == 'tuple'
                or s['type'] == 'set'
                or s['type'] == 'dict'
                or s['type'] == 'frozenset'
            )
            s = s.copy()
            if min_len != 0:
                s['min_length'] = min_len
            if max_len is not None:
                s['max_length'] = max_len

        def check_len(v: Any) -> bool:
            if max_len is not None:
                return (min_len <= len(v)) and (len(v) <= max_len)
            return min_len <= len(v)

        s = _check_func(check_len, f'length >= {min_len} and length <= {max_len}', s)
    elif isinstance(constraint, annotated_types.MultipleOf):
        multiple_of = constraint.multiple_of
        if s and s['type'] in {'int', 'float', 'decimal'}:
            s = s.copy()
            s['multiple_of'] = multiple_of  # pyright: ignore[reportGeneralTypeIssues]
        else:

            def check_multiple_of(v: Any) -> bool:
                return v % multiple_of == 0

            s = _check_func(check_multiple_of, f'% {multiple_of} == 0', s)
    elif isinstance(constraint, annotated_types.Timezone):
        tz = constraint.tz

        if tz is ...:
            if s and s['type'] == 'datetime':
                s = s.copy()
                s['tz_constraint'] = 'aware'
            else:

                def check_tz_aware(v: object) -> bool:
                    assert isinstance(v, datetime.datetime)
                    return v.tzinfo is not None

                s = _check_func(check_tz_aware, 'timezone aware', s)
        elif tz is None:
            if s and s['type'] == 'datetime':
                s = s.copy()
                s['tz_constraint'] = 'naive'
            else:

                def check_tz_naive(v: object) -> bool:
                    assert isinstance(v, datetime.datetime)
                    return v.tzinfo is None

                s = _check_func(check_tz_naive, 'timezone naive', s)
        else:
            raise NotImplementedError('Constraining to a specific timezone is not yet supported')
    elif isinstance(constraint, annotated_types.Interval):
        if constraint.ge is not None:
            s = _apply_constraint(s, annotated_types.Ge(constraint.ge))
        if constraint.gt is not None:
            s = _apply_constraint(s, annotated_types.Gt(constraint.gt))
        if constraint.le is not None:
            s = _apply_constraint(s, annotated_types.Le(constraint.le))
        if constraint.lt is not None:
            s = _apply_constraint(s, annotated_types.Lt(constraint.lt))
        assert s is not None
    elif isinstance(constraint, annotated_types.Predicate):
        func = constraint.func
        # Same logic as in `_known_annotated_metadata.apply_known_metadata()`:
        predicate_name = f'{func.__qualname__!r} ' if hasattr(func, '__qualname__') else ''

        def predicate_func(v: Any) -> Any:
            if not func(v):
                raise PydanticCustomError(
                    'predicate_failed',
                    f'Predicate {predicate_name}failed',  # pyright: ignore[reportArgumentType]
                )
            return v

        if s is None:
            s = cs.no_info_plain_validator_function(predicate_func)
        else:
            s = cs.no_info_after_validator_function(predicate_func, s)
    elif isinstance(constraint, _NotEq):
        value = constraint.value

        def check_not_eq(v: Any) -> bool:
            return operator.__ne__(v, value)

        s = _check_func(check_not_eq, f'!= {value}', s)
    elif isinstance(constraint, _Eq):
        value = constraint.value

        def check_eq(v: Any) -> bool:
            return operator.__eq__(v, value)

        s = _check_func(check_eq, f'== {value}', s)
    elif isinstance(constraint, _In):
        values = constraint.values

        def check_in(v: Any) -> bool:
            return operator.__contains__(values, v)

        s = _check_func(check_in, f'in {values}', s)
    elif isinstance(constraint, _NotIn):
        values = constraint.values

        def check_not_in(v: Any) -> bool:
            return operator.__not__(operator.__contains__(values, v))

        s = _check_func(check_not_in, f'not in {values}', s)
    else:
        assert isinstance(constraint, Pattern)
        if s and s['type'] == 'str':
            s = s.copy()
            s['pattern'] = constraint.pattern
        else:

            def check_pattern(v: object) -> bool:
                assert isinstance(v, str)
                return constraint.match(v) is not None

            s = _check_func(check_pattern, f'~ {constraint.pattern}', s)
    return s


class _SupportsRange(annotated_types.SupportsLe, annotated_types.SupportsGe, Protocol):
    pass


class _SupportsLen(Protocol):
    def __len__(self) -> int: ...


_NewOutGt = TypeVar('_NewOutGt', bound=annotated_types.SupportsGt)
_NewOutGe = TypeVar('_NewOutGe', bound=annotated_types.SupportsGe)
_NewOutLt = TypeVar('_NewOutLt', bound=annotated_types.SupportsLt)
_NewOutLe = TypeVar('_NewOutLe', bound=annotated_types.SupportsLe)
_NewOutLen = TypeVar('_NewOutLen', bound=_SupportsLen)
_NewOutDiv = TypeVar('_NewOutDiv', bound=annotated_types.SupportsDiv)
_NewOutMod = TypeVar('_NewOutMod', bound=annotated_types.SupportsMod)
_NewOutDatetime = TypeVar('_NewOutDatetime', bound=datetime.datetime)
_NewOutInterval = TypeVar('_NewOutInterval', bound=_SupportsRange)
_OtherIn = TypeVar('_OtherIn')
_OtherOut = TypeVar('_OtherOut')
